{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}E:\ISQ log.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}15 Apr 2020, 09:52:56

{com}. logit bias c.pov1##c.biasthreat_labor c.pov1##c.biasthreat_fiscal c.pov1##c.biasthreat_security c.pov1##c.biasthreat_culture female age education sufficient unemployed darabmixed religious, cluster(dst)

{txt}note: pov1 omitted because of collinearity
note: pov1 omitted because of collinearity
note: pov1 omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1288.7349}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1162.9479}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1157.3305}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1157.3127}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1157.3127}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      2311
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}    258.17
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-1157.3127{txt}{col 51}Pseudo R2{col 67}= {res}    0.1020

{txt}{ralign 78:(Std. Err. adjusted for {res:150} clusters in dst)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        bias{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}pov1 {c |}{col 14}{res}{space 2}-.0737643{col 26}{space 2} .1116869{col 37}{space 1}   -0.66{col 46}{space 3}0.509{col 54}{space 4}-.2926665{col 67}{space 3}  .145138
{txt}biasthreat~r {c |}{col 14}{res}{space 2} .5578112{col 26}{space 2} .1261997{col 37}{space 1}    4.42{col 46}{space 3}0.000{col 54}{space 4} .3104645{col 67}{space 3}  .805158
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~r {c |}{col 14}{res}{space 2}  .225454{col 26}{space 2} .1159477{col 37}{space 1}    1.94{col 46}{space 3}0.052{col 54}{space 4}-.0017994{col 67}{space 3} .4527075
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~l {c |}{col 14}{res}{space 2} .3616381{col 26}{space 2}  .115785{col 37}{space 1}    3.12{col 46}{space 3}0.002{col 54}{space 4} .1347036{col 67}{space 3} .5885725
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~l {c |}{col 14}{res}{space 2}-.0335998{col 26}{space 2} .1054402{col 37}{space 1}   -0.32{col 46}{space 3}0.750{col 54}{space 4}-.2402589{col 67}{space 3} .1730592
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~y {c |}{col 14}{res}{space 2} .7127125{col 26}{space 2} .1291557{col 37}{space 1}    5.52{col 46}{space 3}0.000{col 54}{space 4}  .459572{col 67}{space 3}  .965853
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~y {c |}{col 14}{res}{space 2}-.0574189{col 26}{space 2} .1161327{col 37}{space 1}   -0.49{col 46}{space 3}0.621{col 54}{space 4}-.2850348{col 67}{space 3}  .170197
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~e {c |}{col 14}{res}{space 2} .4625327{col 26}{space 2} .1151449{col 37}{space 1}    4.02{col 46}{space 3}0.000{col 54}{space 4} .2368528{col 67}{space 3} .6882127
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~e {c |}{col 14}{res}{space 2}-.2181082{col 26}{space 2} .0984026{col 37}{space 1}   -2.22{col 46}{space 3}0.027{col 54}{space 4}-.4109737{col 67}{space 3}-.0252426
{txt}{space 12} {c |}
{space 6}female {c |}{col 14}{res}{space 2} .1254305{col 26}{space 2} .1059265{col 37}{space 1}    1.18{col 46}{space 3}0.236{col 54}{space 4}-.0821816{col 67}{space 3} .3330426
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0098439{col 26}{space 2}  .004764{col 37}{space 1}    2.07{col 46}{space 3}0.039{col 54}{space 4} .0005066{col 67}{space 3} .0191812
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0104369{col 26}{space 2} .0379075{col 37}{space 1}   -0.28{col 46}{space 3}0.783{col 54}{space 4}-.0847343{col 67}{space 3} .0638605
{txt}{space 2}sufficient {c |}{col 14}{res}{space 2}-.1346038{col 26}{space 2} .0736489{col 37}{space 1}   -1.83{col 46}{space 3}0.068{col 54}{space 4}-.2789531{col 67}{space 3} .0097454
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .0969845{col 26}{space 2}  .180345{col 37}{space 1}    0.54{col 46}{space 3}0.591{col 54}{space 4}-.2564851{col 67}{space 3} .4504541
{txt}{space 2}darabmixed {c |}{col 14}{res}{space 2} .2382125{col 26}{space 2} .1406194{col 37}{space 1}    1.69{col 46}{space 3}0.090{col 54}{space 4}-.0373965{col 67}{space 3} .5138215
{txt}{space 3}religious {c |}{col 14}{res}{space 2}-.3757942{col 26}{space 2} .0910325{col 37}{space 1}   -4.13{col 46}{space 3}0.000{col 54}{space 4}-.5542147{col 67}{space 3}-.1973738
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-1.727041{col 26}{space 2} .4092436{col 37}{space 1}   -4.22{col 46}{space 3}0.000{col 54}{space 4}-2.529143{col 67}{space 3}-.9249379
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. xtmelogit bias c.pov1##c.biasthreat_labor c.pov1##c.biasthreat_fiscal c.pov1##c.biasthreat_security c.pov1##c.biasthreat_culture female age education sufficient unemployed darabmixed religious || dst:
{txt}note: pov1 omitted because of collinearity
note: pov1 omitted because of collinearity
note: pov1 omitted because of collinearity
{res}
{txt}Refining starting values: 
{res}
{txt}Iteration 0:{space 3}log likelihood = {res: -1160.715}  
{res}{txt}Iteration 1:{space 3}log likelihood = {res:-1147.8857}  
{res}{txt}Iteration 2:{space 3}log likelihood = {res:-1145.9623}  
{res}
{txt}Performing gradient-based optimization: 
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-1145.9623}  
{res}{txt}Iteration 1:{space 3}log likelihood = {res:-1145.9476}  
{res}{txt}Iteration 2:{space 3}log likelihood = {res:-1145.9476}  
{res}
{txt}Mixed-effects logistic regression{col 49}Number of obs{col 68}={col 70}{res}     2311
{txt}Group variable: {res}dst{col 49}{txt}Number of groups{col 68}={col 70}{res}      150

{txt}{col 49}Obs per group: min{col 68}={col 70}{res}        9
{txt}{col 64}avg{col 68}={col 70}{res}     15.4
{txt}{col 64}max{col 68}={col 70}{res}       18

{txt}Integration points = {res}  7{col 49}{txt}Wald chi2({res}16{txt}){col 68}={col 70}{res}   207.92
{txt}Log likelihood = {res}-1145.9476{col 49}{txt}Prob > chi2{col 68}={col 73}{res}0.0000

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        bias{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}pov1 {c |}{col 14}{res}{space 2}-.0835986{col 26}{space 2} .1082834{col 37}{space 1}   -0.77{col 46}{space 3}0.440{col 54}{space 4}-.2958303{col 67}{space 3}  .128633
{txt}biasthreat~r {c |}{col 14}{res}{space 2} .6076135{col 26}{space 2} .1256254{col 37}{space 1}    4.84{col 46}{space 3}0.000{col 54}{space 4} .3613924{col 67}{space 3} .8538347
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~r {c |}{col 14}{res}{space 2} .2053304{col 26}{space 2} .1064934{col 37}{space 1}    1.93{col 46}{space 3}0.054{col 54}{space 4}-.0033929{col 67}{space 3} .4140537
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~l {c |}{col 14}{res}{space 2} .4082587{col 26}{space 2} .1216163{col 37}{space 1}    3.36{col 46}{space 3}0.001{col 54}{space 4} .1698952{col 67}{space 3} .6466221
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~l {c |}{col 14}{res}{space 2}-.0104956{col 26}{space 2} .0997297{col 37}{space 1}   -0.11{col 46}{space 3}0.916{col 54}{space 4}-.2059623{col 67}{space 3} .1849711
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~y {c |}{col 14}{res}{space 2} .7264131{col 26}{space 2} .1341099{col 37}{space 1}    5.42{col 46}{space 3}0.000{col 54}{space 4} .4635626{col 67}{space 3} .9892637
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~y {c |}{col 14}{res}{space 2}-.0508981{col 26}{space 2} .1108425{col 37}{space 1}   -0.46{col 46}{space 3}0.646{col 54}{space 4}-.2681454{col 67}{space 3} .1663492
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~e {c |}{col 14}{res}{space 2} .4396235{col 26}{space 2} .1198371{col 37}{space 1}    3.67{col 46}{space 3}0.000{col 54}{space 4} .2047471{col 67}{space 3} .6744998
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~e {c |}{col 14}{res}{space 2}-.2080187{col 26}{space 2} .0981584{col 37}{space 1}   -2.12{col 46}{space 3}0.034{col 54}{space 4}-.4004057{col 67}{space 3}-.0156317
{txt}{space 12} {c |}
{space 6}female {c |}{col 14}{res}{space 2} .1043721{col 26}{space 2} .1089391{col 37}{space 1}    0.96{col 46}{space 3}0.338{col 54}{space 4}-.1091446{col 67}{space 3} .3178887
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0093225{col 26}{space 2} .0045778{col 37}{space 1}    2.04{col 46}{space 3}0.042{col 54}{space 4} .0003502{col 67}{space 3} .0182949
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0315914{col 26}{space 2} .0386219{col 37}{space 1}   -0.82{col 46}{space 3}0.413{col 54}{space 4}-.1072889{col 67}{space 3} .0441061
{txt}{space 2}sufficient {c |}{col 14}{res}{space 2}-.1371406{col 26}{space 2} .0776196{col 37}{space 1}   -1.77{col 46}{space 3}0.077{col 54}{space 4}-.2892721{col 67}{space 3} .0149909
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .1727984{col 26}{space 2} .2106965{col 37}{space 1}    0.82{col 46}{space 3}0.412{col 54}{space 4}-.2401591{col 67}{space 3} .5857559
{txt}{space 2}darabmixed {c |}{col 14}{res}{space 2} .1877855{col 26}{space 2} .1362963{col 37}{space 1}    1.38{col 46}{space 3}0.168{col 54}{space 4}-.0793503{col 67}{space 3} .4549212
{txt}{space 3}religious {c |}{col 14}{res}{space 2}-.3542223{col 26}{space 2} .0925907{col 37}{space 1}   -3.83{col 46}{space 3}0.000{col 54}{space 4}-.5356967{col 67}{space 3}-.1727479
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-1.738367{col 26}{space 2} .4172817{col 37}{space 1}   -4.17{col 46}{space 3}0.000{col 54}{space 4}-2.556224{col 67}{space 3}-.9205094
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{hline 29}{c TT}{hline 48}
{col 3}Random-effects Parameters{col 30}{c |}{col 34}Estimate{col 45}Std. Err.{col 59}[95% Conf. Interval]
{hline 29}{c +}{hline 48}
{res}dst{txt}: Identity{col 30}{c |}
{col 20}sd(_cons){col 30}{c |}{res}{col 33} .5387358{col 44} .0835952{col 58} .3974621{col 70} .7302239
{txt}{hline 29}{c BT}{hline 48}
LR test vs. logistic regression:{col 34}{help j_chibar##|_new:chibar2(01) =}{col 48}{res}   22.73{col 57}{txt}Prob>=chibar2 = {col 73}{res}0.0000

{com}. 
. 
. 
. logit bias c.pov1##c.sufficient##c.biasthreat_labor biasthreat_fiscal biasthreat_security biasthreat_culture female age education unemployed darabmixed religious, cluster(dst)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1288.7349}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1164.4789}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1157.7804}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1157.7319}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1157.7319}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      2311
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}    240.53
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-1157.7319{txt}{col 51}Pseudo R2{col 67}= {res}    0.1017

{txt}{ralign 78:(Std. Err. adjusted for {res:150} clusters in dst)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        bias{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}pov1 {c |}{col 14}{res}{space 2}-.9071046{col 26}{space 2} .2502011{col 37}{space 1}   -3.63{col 46}{space 3}0.000{col 54}{space 4} -1.39749{col 67}{space 3}-.4167195
{txt}{space 2}sufficient {c |}{col 14}{res}{space 2}-.0086747{col 26}{space 2} .1018352{col 37}{space 1}   -0.09{col 46}{space 3}0.932{col 54}{space 4} -.208268{col 67}{space 3} .1909185
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
c.sufficient {c |}{col 14}{res}{space 2} .2457926{col 26}{space 2} .0814761{col 37}{space 1}    3.02{col 46}{space 3}0.003{col 54}{space 4} .0861023{col 67}{space 3} .4054828
{txt}{space 12} {c |}
biasthreat~r {c |}{col 14}{res}{space 2} .9771422{col 26}{space 2} .3840175{col 37}{space 1}    2.54{col 46}{space 3}0.011{col 54}{space 4} .2244818{col 67}{space 3} 1.729803
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~r {c |}{col 14}{res}{space 2}  .782824{col 26}{space 2} .3063894{col 37}{space 1}    2.55{col 46}{space 3}0.011{col 54}{space 4} .1823118{col 67}{space 3} 1.383336
{txt}{space 12} {c |}
{space 10}c. {c |}
{space 2}sufficient#{c |}
{space 10}c. {c |}
biasthreat~r {c |}{col 14}{res}{space 2}-.1696955{col 26}{space 2} .1314597{col 37}{space 1}   -1.29{col 46}{space 3}0.197{col 54}{space 4}-.4273517{col 67}{space 3} .0879607
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
{space 2}sufficient#{c |}
{space 10}c. {c |}
biasthreat~r {c |}{col 14}{res}{space 2}-.2276437{col 26}{space 2} .1101591{col 37}{space 1}   -2.07{col 46}{space 3}0.039{col 54}{space 4}-.4435517{col 67}{space 3}-.0117358
{txt}{space 12} {c |}
biasthreat~l {c |}{col 14}{res}{space 2} .3654636{col 26}{space 2} .1121768{col 37}{space 1}    3.26{col 46}{space 3}0.001{col 54}{space 4} .1456011{col 67}{space 3}  .585326
{txt}biasthreat~y {c |}{col 14}{res}{space 2} .7451074{col 26}{space 2} .1231274{col 37}{space 1}    6.05{col 46}{space 3}0.000{col 54}{space 4} .5037822{col 67}{space 3} .9864327
{txt}biasthreat~e {c |}{col 14}{res}{space 2} .5027007{col 26}{space 2} .1141685{col 37}{space 1}    4.40{col 46}{space 3}0.000{col 54}{space 4} .2789345{col 67}{space 3} .7264669
{txt}{space 6}female {c |}{col 14}{res}{space 2} .1205318{col 26}{space 2} .1052927{col 37}{space 1}    1.14{col 46}{space 3}0.252{col 54}{space 4}-.0858381{col 67}{space 3} .3269018
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0098388{col 26}{space 2} .0047497{col 37}{space 1}    2.07{col 46}{space 3}0.038{col 54}{space 4} .0005295{col 67}{space 3} .0191482
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0130848{col 26}{space 2} .0379003{col 37}{space 1}   -0.35{col 46}{space 3}0.730{col 54}{space 4}-.0873681{col 67}{space 3} .0611985
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .1199949{col 26}{space 2} .1809929{col 37}{space 1}    0.66{col 46}{space 3}0.507{col 54}{space 4}-.2347447{col 67}{space 3} .4747346
{txt}{space 2}darabmixed {c |}{col 14}{res}{space 2} .2544693{col 26}{space 2} .1401936{col 37}{space 1}    1.82{col 46}{space 3}0.070{col 54}{space 4} -.020305{col 67}{space 3} .5292437
{txt}{space 3}religious {c |}{col 14}{res}{space 2}-.3713827{col 26}{space 2} .0891012{col 37}{space 1}   -4.17{col 46}{space 3}0.000{col 54}{space 4}-.5460179{col 67}{space 3}-.1967475
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-2.103994{col 26}{space 2} .4622175{col 37}{space 1}   -4.55{col 46}{space 3}0.000{col 54}{space 4}-3.009923{col 67}{space 3}-1.198064
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. logit bias c.pov1##c.sufficient##c.biasthreat_fiscal biasthreat_labor biasthreat_security biasthreat_culture female age education unemployed darabmixed religious, cluster(dst)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1288.7349}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1166.4472}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1161.1587}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1161.1432}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1161.1432}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      2311
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}    233.32
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-1161.1432{txt}{col 51}Pseudo R2{col 67}= {res}    0.0990

{txt}{ralign 78:(Std. Err. adjusted for {res:150} clusters in dst)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        bias{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}pov1 {c |}{col 14}{res}{space 2} -.330616{col 26}{space 2} .2462712{col 37}{space 1}   -1.34{col 46}{space 3}0.179{col 54}{space 4}-.8132986{col 67}{space 3} .1520667
{txt}{space 2}sufficient {c |}{col 14}{res}{space 2}-.1108829{col 26}{space 2} .1023741{col 37}{space 1}   -1.08{col 46}{space 3}0.279{col 54}{space 4}-.3115324{col 67}{space 3} .0897666
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
c.sufficient {c |}{col 14}{res}{space 2} .0818089{col 26}{space 2} .0833549{col 37}{space 1}    0.98{col 46}{space 3}0.326{col 54}{space 4}-.0815637{col 67}{space 3} .2451815
{txt}{space 12} {c |}
biasthreat~l {c |}{col 14}{res}{space 2} .4659599{col 26}{space 2} .4279411{col 37}{space 1}    1.09{col 46}{space 3}0.276{col 54}{space 4}-.3727893{col 67}{space 3} 1.304709
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~l {c |}{col 14}{res}{space 2}-.0551407{col 26}{space 2} .3187128{col 37}{space 1}   -0.17{col 46}{space 3}0.863{col 54}{space 4}-.6798064{col 67}{space 3}  .569525
{txt}{space 12} {c |}
{space 10}c. {c |}
{space 2}sufficient#{c |}
{space 10}c. {c |}
biasthreat~l {c |}{col 14}{res}{space 2}-.0355745{col 26}{space 2} .1477871{col 37}{space 1}   -0.24{col 46}{space 3}0.810{col 54}{space 4}-.3252319{col 67}{space 3} .2540829
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
{space 2}sufficient#{c |}
{space 10}c. {c |}
biasthreat~l {c |}{col 14}{res}{space 2} .0085784{col 26}{space 2} .1100359{col 37}{space 1}    0.08{col 46}{space 3}0.938{col 54}{space 4} -.207088{col 67}{space 3} .2242448
{txt}{space 12} {c |}
biasthreat~r {c |}{col 14}{res}{space 2} .4899165{col 26}{space 2} .1219199{col 37}{space 1}    4.02{col 46}{space 3}0.000{col 54}{space 4} .2509578{col 67}{space 3} .7288751
{txt}biasthreat~y {c |}{col 14}{res}{space 2} .7443206{col 26}{space 2}  .122889{col 37}{space 1}    6.06{col 46}{space 3}0.000{col 54}{space 4} .5034625{col 67}{space 3} .9851786
{txt}biasthreat~e {c |}{col 14}{res}{space 2} .5076219{col 26}{space 2} .1139563{col 37}{space 1}    4.45{col 46}{space 3}0.000{col 54}{space 4} .2842717{col 67}{space 3} .7309722
{txt}{space 6}female {c |}{col 14}{res}{space 2} .1166876{col 26}{space 2} .1060068{col 37}{space 1}    1.10{col 46}{space 3}0.271{col 54}{space 4} -.091082{col 67}{space 3} .3244572
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0100048{col 26}{space 2} .0047875{col 37}{space 1}    2.09{col 46}{space 3}0.037{col 54}{space 4} .0006215{col 67}{space 3}  .019388
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0100776{col 26}{space 2}  .038424{col 37}{space 1}   -0.26{col 46}{space 3}0.793{col 54}{space 4}-.0853872{col 67}{space 3}  .065232
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .0958113{col 26}{space 2} .1826257{col 37}{space 1}    0.52{col 46}{space 3}0.600{col 54}{space 4}-.2621285{col 67}{space 3} .4537511
{txt}{space 2}darabmixed {c |}{col 14}{res}{space 2} .2511324{col 26}{space 2} .1407543{col 37}{space 1}    1.78{col 46}{space 3}0.074{col 54}{space 4} -.024741{col 67}{space 3} .5270058
{txt}{space 3}religious {c |}{col 14}{res}{space 2} -.373792{col 26}{space 2} .0888069{col 37}{space 1}   -4.21{col 46}{space 3}0.000{col 54}{space 4}-.5478503{col 67}{space 3}-.1997337
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-1.813546{col 26}{space 2} .4555648{col 37}{space 1}   -3.98{col 46}{space 3}0.000{col 54}{space 4}-2.706437{col 67}{space 3}-.9206558
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. logit bias c.pov1##c.sufficient##c.biasthreat_security biasthreat_labor biasthreat_fiscal biasthreat_culture female age education unemployed darabmixed religious, cluster(dst)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1288.7349}  
Iteration 1:{space 3}log pseudolikelihood = {res: -1165.214}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1159.0746}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1159.0532}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1159.0532}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      2311
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}    237.46
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-1159.0532{txt}{col 51}Pseudo R2{col 67}= {res}    0.1006

{txt}{ralign 78:(Std. Err. adjusted for {res:150} clusters in dst)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        bias{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}pov1 {c |}{col 14}{res}{space 2}-.8404545{col 26}{space 2} .3124642{col 37}{space 1}   -2.69{col 46}{space 3}0.007{col 54}{space 4}-1.452873{col 67}{space 3}-.2280359
{txt}{space 2}sufficient {c |}{col 14}{res}{space 2}-.2016812{col 26}{space 2} .1355522{col 37}{space 1}   -1.49{col 46}{space 3}0.137{col 54}{space 4}-.4673587{col 67}{space 3} .0639963
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
c.sufficient {c |}{col 14}{res}{space 2} .2674958{col 26}{space 2} .1023233{col 37}{space 1}    2.61{col 46}{space 3}0.009{col 54}{space 4} .0669458{col 67}{space 3} .4680458
{txt}{space 12} {c |}
biasthreat~y {c |}{col 14}{res}{space 2} .4740535{col 26}{space 2} .4960181{col 37}{space 1}    0.96{col 46}{space 3}0.339{col 54}{space 4}-.4981242{col 67}{space 3} 1.446231
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~y {c |}{col 14}{res}{space 2}  .654732{col 26}{space 2} .3680756{col 37}{space 1}    1.78{col 46}{space 3}0.075{col 54}{space 4}-.0666829{col 67}{space 3} 1.376147
{txt}{space 12} {c |}
{space 10}c. {c |}
{space 2}sufficient#{c |}
{space 10}c. {c |}
biasthreat~y {c |}{col 14}{res}{space 2} .0967775{col 26}{space 2} .1746791{col 37}{space 1}    0.55{col 46}{space 3}0.580{col 54}{space 4}-.2455873{col 67}{space 3} .4391423
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
{space 2}sufficient#{c |}
{space 10}c. {c |}
biasthreat~y {c |}{col 14}{res}{space 2}-.2462059{col 26}{space 2} .1265366{col 37}{space 1}   -1.95{col 46}{space 3}0.052{col 54}{space 4} -.494213{col 67}{space 3} .0018013
{txt}{space 12} {c |}
biasthreat~r {c |}{col 14}{res}{space 2} .4849685{col 26}{space 2} .1227642{col 37}{space 1}    3.95{col 46}{space 3}0.000{col 54}{space 4}  .244355{col 67}{space 3} .7255819
{txt}biasthreat~l {c |}{col 14}{res}{space 2} .3751752{col 26}{space 2} .1125529{col 37}{space 1}    3.33{col 46}{space 3}0.001{col 54}{space 4} .1545757{col 67}{space 3} .5957748
{txt}biasthreat~e {c |}{col 14}{res}{space 2} .5009052{col 26}{space 2} .1155763{col 37}{space 1}    4.33{col 46}{space 3}0.000{col 54}{space 4} .2743798{col 67}{space 3} .7274305
{txt}{space 6}female {c |}{col 14}{res}{space 2} .1138216{col 26}{space 2} .1056483{col 37}{space 1}    1.08{col 46}{space 3}0.281{col 54}{space 4}-.0932453{col 67}{space 3} .3208885
{txt}{space 9}age {c |}{col 14}{res}{space 2}  .009846{col 26}{space 2} .0047599{col 37}{space 1}    2.07{col 46}{space 3}0.039{col 54}{space 4} .0005167{col 67}{space 3} .0191752
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0114829{col 26}{space 2}  .037993{col 37}{space 1}   -0.30{col 46}{space 3}0.762{col 54}{space 4}-.0859478{col 67}{space 3}  .062982
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .0953293{col 26}{space 2} .1806266{col 37}{space 1}    0.53{col 46}{space 3}0.598{col 54}{space 4}-.2586923{col 67}{space 3} .4493509
{txt}{space 2}darabmixed {c |}{col 14}{res}{space 2} .2507658{col 26}{space 2} .1396107{col 37}{space 1}    1.80{col 46}{space 3}0.072{col 54}{space 4}-.0228661{col 67}{space 3} .5243978
{txt}{space 3}religious {c |}{col 14}{res}{space 2}-.3728579{col 26}{space 2} .0886323{col 37}{space 1}   -4.21{col 46}{space 3}0.000{col 54}{space 4}-.5465741{col 67}{space 3}-.1991417
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-1.552929{col 26}{space 2} .5340707{col 37}{space 1}   -2.91{col 46}{space 3}0.004{col 54}{space 4}-2.599688{col 67}{space 3}-.5061694
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. logit bias c.pov1##c.sufficient##c.biasthreat_culture biasthreat_labor biasthreat_fiscal biasthreat_security female age education unemployed darabmixed religious, cluster(dst)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1288.7349}  
Iteration 1:{space 3}log pseudolikelihood = {res: -1162.202}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1156.6241}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1156.6091}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1156.6091}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      2311
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}    257.61
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-1156.6091{txt}{col 51}Pseudo R2{col 67}= {res}    0.1025

{txt}{ralign 78:(Std. Err. adjusted for {res:150} clusters in dst)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        bias{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}pov1 {c |}{col 14}{res}{space 2}-.6295837{col 26}{space 2} .2797409{col 37}{space 1}   -2.25{col 46}{space 3}0.024{col 54}{space 4}-1.177866{col 67}{space 3}-.0813017
{txt}{space 2}sufficient {c |}{col 14}{res}{space 2}-.0528927{col 26}{space 2} .1327778{col 37}{space 1}   -0.40{col 46}{space 3}0.690{col 54}{space 4}-.3131323{col 67}{space 3} .2073469
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
c.sufficient {c |}{col 14}{res}{space 2} .2490032{col 26}{space 2} .1009578{col 37}{space 1}    2.47{col 46}{space 3}0.014{col 54}{space 4} .0511295{col 67}{space 3} .4468769
{txt}{space 12} {c |}
biasthreat~e {c |}{col 14}{res}{space 2} .6825751{col 26}{space 2} .4631559{col 37}{space 1}    1.47{col 46}{space 3}0.141{col 54}{space 4}-.2251937{col 67}{space 3} 1.590344
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~e {c |}{col 14}{res}{space 2} .3391536{col 26}{space 2} .3506749{col 37}{space 1}    0.97{col 46}{space 3}0.333{col 54}{space 4}-.3481565{col 67}{space 3} 1.026464
{txt}{space 12} {c |}
{space 10}c. {c |}
{space 2}sufficient#{c |}
{space 10}c. {c |}
biasthreat~e {c |}{col 14}{res}{space 2}-.0913583{col 26}{space 2} .1601727{col 37}{space 1}   -0.57{col 46}{space 3}0.568{col 54}{space 4} -.405291{col 67}{space 3} .2225745
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
{space 2}sufficient#{c |}
{space 10}c. {c |}
biasthreat~e {c |}{col 14}{res}{space 2}-.2149015{col 26}{space 2} .1243228{col 37}{space 1}   -1.73{col 46}{space 3}0.084{col 54}{space 4}-.4585696{col 67}{space 3} .0287667
{txt}{space 12} {c |}
biasthreat~r {c |}{col 14}{res}{space 2} .5070625{col 26}{space 2} .1207901{col 37}{space 1}    4.20{col 46}{space 3}0.000{col 54}{space 4} .2703183{col 67}{space 3} .7438068
{txt}biasthreat~l {c |}{col 14}{res}{space 2} .3715611{col 26}{space 2} .1135038{col 37}{space 1}    3.27{col 46}{space 3}0.001{col 54}{space 4} .1490977{col 67}{space 3} .5940245
{txt}biasthreat~y {c |}{col 14}{res}{space 2} .7457354{col 26}{space 2}  .122251{col 37}{space 1}    6.10{col 46}{space 3}0.000{col 54}{space 4} .5061278{col 67}{space 3} .9853429
{txt}{space 6}female {c |}{col 14}{res}{space 2} .1199911{col 26}{space 2} .1060766{col 37}{space 1}    1.13{col 46}{space 3}0.258{col 54}{space 4}-.0879153{col 67}{space 3} .3278975
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0101498{col 26}{space 2} .0047359{col 37}{space 1}    2.14{col 46}{space 3}0.032{col 54}{space 4} .0008675{col 67}{space 3} .0194321
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0079314{col 26}{space 2} .0381816{col 37}{space 1}   -0.21{col 46}{space 3}0.835{col 54}{space 4}-.0827658{col 67}{space 3} .0669031
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .0962211{col 26}{space 2} .1809795{col 37}{space 1}    0.53{col 46}{space 3}0.595{col 54}{space 4}-.2584923{col 67}{space 3} .4509345
{txt}{space 2}darabmixed {c |}{col 14}{res}{space 2} .2381059{col 26}{space 2} .1397311{col 37}{space 1}    1.70{col 46}{space 3}0.088{col 54}{space 4} -.035762{col 67}{space 3} .5119737
{txt}{space 3}religious {c |}{col 14}{res}{space 2}-.3782387{col 26}{space 2} .0901148{col 37}{space 1}   -4.20{col 46}{space 3}0.000{col 54}{space 4}-.5548605{col 67}{space 3}-.2016169
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-1.919717{col 26}{space 2} .5218402{col 37}{space 1}   -3.68{col 46}{space 3}0.000{col 54}{space 4}-2.942505{col 67}{space 3}-.8969288
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. 
. 
. logit bias c.pov1##c.biasthreat_labor c.pov1##c.biasthreat_fiscal c.pov1##c.biasthreat_security c.pov1##c.biasthreat_culture##c.biaspanarab female age education sufficient unemployed darabmixed religious, cluster(dst)

{txt}note: pov1 omitted because of collinearity
note: pov1 omitted because of collinearity
note: pov1 omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1130.9223}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1006.1037}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1000.5737}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1000.5515}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1000.5515}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      1999
{txt}{col 51}Wald chi2({res}20{txt}){col 67}= {res}    220.68
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-1000.5515{txt}{col 51}Pseudo R2{col 67}= {res}    0.1153

{txt}{ralign 78:(Std. Err. adjusted for {res:150} clusters in dst)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        bias{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}pov1 {c |}{col 14}{res}{space 2}-.0525785{col 26}{space 2}  .125868{col 37}{space 1}   -0.42{col 46}{space 3}0.676{col 54}{space 4}-.2992753{col 67}{space 3} .1941183
{txt}biasthreat~r {c |}{col 14}{res}{space 2} .5043546{col 26}{space 2} .1308833{col 37}{space 1}    3.85{col 46}{space 3}0.000{col 54}{space 4}  .247828{col 67}{space 3} .7608811
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~r {c |}{col 14}{res}{space 2}  .076532{col 26}{space 2} .1259175{col 37}{space 1}    0.61{col 46}{space 3}0.543{col 54}{space 4}-.1702619{col 67}{space 3} .3233258
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~l {c |}{col 14}{res}{space 2}  .429085{col 26}{space 2}  .127935{col 37}{space 1}    3.35{col 46}{space 3}0.001{col 54}{space 4} .1783371{col 67}{space 3} .6798329
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~l {c |}{col 14}{res}{space 2}-.0000444{col 26}{space 2} .1263052{col 37}{space 1}   -0.00{col 46}{space 3}1.000{col 54}{space 4}-.2475981{col 67}{space 3} .2475093
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~y {c |}{col 14}{res}{space 2}   .64798{col 26}{space 2} .1456547{col 37}{space 1}    4.45{col 46}{space 3}0.000{col 54}{space 4} .3625021{col 67}{space 3}  .933458
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~y {c |}{col 14}{res}{space 2}-.0419694{col 26}{space 2} .1322228{col 37}{space 1}   -0.32{col 46}{space 3}0.751{col 54}{space 4}-.3011212{col 67}{space 3} .2171825
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~e {c |}{col 14}{res}{space 2} .4442409{col 26}{space 2} .1330021{col 37}{space 1}    3.34{col 46}{space 3}0.001{col 54}{space 4} .1835614{col 67}{space 3} .7049203
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~e {c |}{col 14}{res}{space 2}  -.19702{col 26}{space 2} .1114036{col 37}{space 1}   -1.77{col 46}{space 3}0.077{col 54}{space 4} -.415367{col 67}{space 3} .0213271
{txt}{space 12} {c |}
{space 1}biaspanarab {c |}{col 14}{res}{space 2} 1.169226{col 26}{space 2} .2733353{col 37}{space 1}    4.28{col 46}{space 3}0.000{col 54}{space 4} .6334988{col 67}{space 3} 1.704954
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
{space 1}biaspanarab {c |}{col 14}{res}{space 2} .1780922{col 26}{space 2} .2268432{col 37}{space 1}    0.79{col 46}{space 3}0.432{col 54}{space 4}-.2665122{col 67}{space 3} .6226966
{txt}{space 12} {c |}
{space 10}c. {c |}
biasthreat~e#{c |}
{space 10}c. {c |}
{space 1}biaspanarab {c |}{col 14}{res}{space 2}-.4824406{col 26}{space 2}  .332661{col 37}{space 1}   -1.45{col 46}{space 3}0.147{col 54}{space 4}-1.134444{col 67}{space 3} .1695631
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~e#{c |}
{space 10}c. {c |}
{space 1}biaspanarab {c |}{col 14}{res}{space 2}-.0449657{col 26}{space 2} .2723334{col 37}{space 1}   -0.17{col 46}{space 3}0.869{col 54}{space 4}-.5787294{col 67}{space 3} .4887979
{txt}{space 12} {c |}
{space 6}female {c |}{col 14}{res}{space 2} .1424376{col 26}{space 2} .1126911{col 37}{space 1}    1.26{col 46}{space 3}0.206{col 54}{space 4}-.0784328{col 67}{space 3} .3633081
{txt}{space 9}age {c |}{col 14}{res}{space 2}  .011605{col 26}{space 2} .0052521{col 37}{space 1}    2.21{col 46}{space 3}0.027{col 54}{space 4}  .001311{col 67}{space 3}  .021899
{txt}{space 3}education {c |}{col 14}{res}{space 2}  .013078{col 26}{space 2} .0419078{col 37}{space 1}    0.31{col 46}{space 3}0.755{col 54}{space 4}-.0690597{col 67}{space 3} .0952156
{txt}{space 2}sufficient {c |}{col 14}{res}{space 2} -.133574{col 26}{space 2} .0853354{col 37}{space 1}   -1.57{col 46}{space 3}0.118{col 54}{space 4}-.3008283{col 67}{space 3} .0336803
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .1769038{col 26}{space 2} .1934732{col 37}{space 1}    0.91{col 46}{space 3}0.361{col 54}{space 4}-.2022966{col 67}{space 3} .5561043
{txt}{space 2}darabmixed {c |}{col 14}{res}{space 2} .2203549{col 26}{space 2} .1560642{col 37}{space 1}    1.41{col 46}{space 3}0.158{col 54}{space 4}-.0855254{col 67}{space 3} .5262352
{txt}{space 3}religious {c |}{col 14}{res}{space 2}-.3510186{col 26}{space 2}  .098694{col 37}{space 1}   -3.56{col 46}{space 3}0.000{col 54}{space 4}-.5444553{col 67}{space 3}-.1575819
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-1.970305{col 26}{space 2} .4668138{col 37}{space 1}   -4.22{col 46}{space 3}0.000{col 54}{space 4}-2.885244{col 67}{space 3}-1.055367
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. logit bias c.pov1##c.biasthreat_labor c.pov1##c.biasthreat_fiscal c.pov1##c.biasthreat_security c.pov1##c.biasthreat_culture female age education income unemployed darabmixed religious, cluster(dst)

{txt}note: pov1 omitted because of collinearity
note: pov1 omitted because of collinearity
note: pov1 omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1108.9716}  
Iteration 1:{space 3}log pseudolikelihood = {res:-995.88371}  
Iteration 2:{space 3}log pseudolikelihood = {res:-990.76352}  
Iteration 3:{space 3}log pseudolikelihood = {res:-990.74812}  
Iteration 4:{space 3}log pseudolikelihood = {res:-990.74812}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      1976
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}    222.07
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-990.74812{txt}{col 51}Pseudo R2{col 67}= {res}    0.1066

{txt}{ralign 78:(Std. Err. adjusted for {res:150} clusters in dst)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        bias{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}pov1 {c |}{col 14}{res}{space 2}-.0622766{col 26}{space 2} .1215865{col 37}{space 1}   -0.51{col 46}{space 3}0.609{col 54}{space 4}-.3005817{col 67}{space 3} .1760285
{txt}biasthreat~r {c |}{col 14}{res}{space 2} .6362303{col 26}{space 2} .1401558{col 37}{space 1}    4.54{col 46}{space 3}0.000{col 54}{space 4}   .36153{col 67}{space 3} .9109306
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~r {c |}{col 14}{res}{space 2} .2299815{col 26}{space 2} .1334695{col 37}{space 1}    1.72{col 46}{space 3}0.085{col 54}{space 4}-.0316138{col 67}{space 3} .4915769
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~l {c |}{col 14}{res}{space 2} .3406203{col 26}{space 2} .1377073{col 37}{space 1}    2.47{col 46}{space 3}0.013{col 54}{space 4} .0707189{col 67}{space 3} .6105217
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~l {c |}{col 14}{res}{space 2} .0215411{col 26}{space 2} .1339227{col 37}{space 1}    0.16{col 46}{space 3}0.872{col 54}{space 4}-.2409425{col 67}{space 3} .2840247
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~y {c |}{col 14}{res}{space 2} .6825009{col 26}{space 2} .1451127{col 37}{space 1}    4.70{col 46}{space 3}0.000{col 54}{space 4} .3980852{col 67}{space 3} .9669166
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~y {c |}{col 14}{res}{space 2}-.0674895{col 26}{space 2} .1262702{col 37}{space 1}   -0.53{col 46}{space 3}0.593{col 54}{space 4}-.3149746{col 67}{space 3} .1799956
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~e {c |}{col 14}{res}{space 2} .4482492{col 26}{space 2} .1273561{col 37}{space 1}    3.52{col 46}{space 3}0.000{col 54}{space 4} .1986359{col 67}{space 3} .6978625
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~e {c |}{col 14}{res}{space 2}-.2663464{col 26}{space 2} .1072336{col 37}{space 1}   -2.48{col 46}{space 3}0.013{col 54}{space 4}-.4765203{col 67}{space 3}-.0561724
{txt}{space 12} {c |}
{space 6}female {c |}{col 14}{res}{space 2} .0581921{col 26}{space 2} .1186555{col 37}{space 1}    0.49{col 46}{space 3}0.624{col 54}{space 4}-.1743684{col 67}{space 3} .2907526
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0088092{col 26}{space 2} .0051765{col 37}{space 1}    1.70{col 46}{space 3}0.089{col 54}{space 4}-.0013366{col 67}{space 3} .0189551
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0038007{col 26}{space 2} .0423544{col 37}{space 1}   -0.09{col 46}{space 3}0.928{col 54}{space 4}-.0868138{col 67}{space 3} .0792125
{txt}{space 6}income {c |}{col 14}{res}{space 2}-.1155992{col 26}{space 2}  .074306{col 37}{space 1}   -1.56{col 46}{space 3}0.120{col 54}{space 4}-.2612363{col 67}{space 3} .0300379
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .1499703{col 26}{space 2} .1959699{col 37}{space 1}    0.77{col 46}{space 3}0.444{col 54}{space 4}-.2341236{col 67}{space 3} .5340642
{txt}{space 2}darabmixed {c |}{col 14}{res}{space 2} .3417355{col 26}{space 2} .1550262{col 37}{space 1}    2.20{col 46}{space 3}0.027{col 54}{space 4} .0378897{col 67}{space 3} .6455813
{txt}{space 3}religious {c |}{col 14}{res}{space 2}-.3552185{col 26}{space 2} .0980314{col 37}{space 1}   -3.62{col 46}{space 3}0.000{col 54}{space 4}-.5473566{col 67}{space 3}-.1630804
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-1.925402{col 26}{space 2} .4086999{col 37}{space 1}   -4.71{col 46}{space 3}0.000{col 54}{space 4}-2.726439{col 67}{space 3}-1.124365
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. logit bias c.pov1##c.biasthreat_labor c.pov1##c.biasthreat_fiscal c.pov1##c.biasthreat_security c.pov1##c.biasthreat_culture female age education ecoself unemployed darabmixed religious, cluster(dst)

{txt}note: pov1 omitted because of collinearity
note: pov1 omitted because of collinearity
note: pov1 omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1305.0168}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1177.5853}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1171.9599}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1171.9409}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1171.9409}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      2333
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}    267.30
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-1171.9409{txt}{col 51}Pseudo R2{col 67}= {res}    0.1020

{txt}{ralign 78:(Std. Err. adjusted for {res:150} clusters in dst)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        bias{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}pov1 {c |}{col 14}{res}{space 2}-.0821842{col 26}{space 2} .1114005{col 37}{space 1}   -0.74{col 46}{space 3}0.461{col 54}{space 4}-.3005251{col 67}{space 3} .1361567
{txt}biasthreat~r {c |}{col 14}{res}{space 2} .5559264{col 26}{space 2} .1235585{col 37}{space 1}    4.50{col 46}{space 3}0.000{col 54}{space 4} .3137562{col 67}{space 3} .7980966
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~r {c |}{col 14}{res}{space 2} .2108168{col 26}{space 2} .1144234{col 37}{space 1}    1.84{col 46}{space 3}0.065{col 54}{space 4} -.013449{col 67}{space 3} .4350825
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~l {c |}{col 14}{res}{space 2} .3683058{col 26}{space 2} .1168367{col 37}{space 1}    3.15{col 46}{space 3}0.002{col 54}{space 4} .1393101{col 67}{space 3} .5973016
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~l {c |}{col 14}{res}{space 2}-.0054218{col 26}{space 2} .1067454{col 37}{space 1}   -0.05{col 46}{space 3}0.959{col 54}{space 4}-.2146389{col 67}{space 3} .2037954
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~y {c |}{col 14}{res}{space 2} .7008537{col 26}{space 2} .1280408{col 37}{space 1}    5.47{col 46}{space 3}0.000{col 54}{space 4} .4498982{col 67}{space 3} .9518091
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~y {c |}{col 14}{res}{space 2}-.0458819{col 26}{space 2} .1127946{col 37}{space 1}   -0.41{col 46}{space 3}0.684{col 54}{space 4}-.2669553{col 67}{space 3} .1751914
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~e {c |}{col 14}{res}{space 2} .4564381{col 26}{space 2} .1127797{col 37}{space 1}    4.05{col 46}{space 3}0.000{col 54}{space 4}  .235394{col 67}{space 3} .6774823
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~e {c |}{col 14}{res}{space 2}-.2292987{col 26}{space 2} .0941878{col 37}{space 1}   -2.43{col 46}{space 3}0.015{col 54}{space 4}-.4139034{col 67}{space 3}-.0446941
{txt}{space 12} {c |}
{space 6}female {c |}{col 14}{res}{space 2} .1223928{col 26}{space 2} .1085618{col 37}{space 1}    1.13{col 46}{space 3}0.260{col 54}{space 4}-.0903846{col 67}{space 3} .3351701
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0095827{col 26}{space 2} .0047029{col 37}{space 1}    2.04{col 46}{space 3}0.042{col 54}{space 4} .0003651{col 67}{space 3} .0188002
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0217775{col 26}{space 2} .0377834{col 37}{space 1}   -0.58{col 46}{space 3}0.564{col 54}{space 4}-.0958315{col 67}{space 3} .0522766
{txt}{space 5}ecoself {c |}{col 14}{res}{space 2} .0778987{col 26}{space 2} .0897821{col 37}{space 1}    0.87{col 46}{space 3}0.386{col 54}{space 4} -.098071{col 67}{space 3} .2538683
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .1244348{col 26}{space 2} .1802723{col 37}{space 1}    0.69{col 46}{space 3}0.490{col 54}{space 4}-.2288924{col 67}{space 3} .4777621
{txt}{space 2}darabmixed {c |}{col 14}{res}{space 2} .2842751{col 26}{space 2} .1347075{col 37}{space 1}    2.11{col 46}{space 3}0.035{col 54}{space 4} .0202532{col 67}{space 3}  .548297
{txt}{space 3}religious {c |}{col 14}{res}{space 2}-.3866986{col 26}{space 2} .0915413{col 37}{space 1}   -4.22{col 46}{space 3}0.000{col 54}{space 4}-.5661163{col 67}{space 3}-.2072809
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-2.222639{col 26}{space 2} .4444682{col 37}{space 1}   -5.00{col 46}{space 3}0.000{col 54}{space 4} -3.09378{col 67}{space 3}-1.351497
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. logit bias c.pov1##c.biasthreat_labor c.pov1##c.biasthreat_fiscal c.pov1##c.biasthreat_security c.pov1##c.biasthreat_culture female age education room unemployed darabmixed religious, cluster(dst)

{txt}note: pov1 omitted because of collinearity
note: pov1 omitted because of collinearity
note: pov1 omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1340.0812}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1204.9953}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1198.9132}  
Iteration 3:{space 3}log pseudolikelihood = {res: -1198.894}  
Iteration 4:{space 3}log pseudolikelihood = {res: -1198.894}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      2386
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}    272.46
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res} -1198.894{txt}{col 51}Pseudo R2{col 67}= {res}    0.1054

{txt}{ralign 78:(Std. Err. adjusted for {res:150} clusters in dst)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        bias{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}pov1 {c |}{col 14}{res}{space 2}-.0493334{col 26}{space 2} .1097639{col 37}{space 1}   -0.45{col 46}{space 3}0.653{col 54}{space 4}-.2644668{col 67}{space 3}    .1658
{txt}biasthreat~r {c |}{col 14}{res}{space 2} .5432026{col 26}{space 2} .1234394{col 37}{space 1}    4.40{col 46}{space 3}0.000{col 54}{space 4} .3012657{col 67}{space 3} .7851394
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~r {c |}{col 14}{res}{space 2}  .213816{col 26}{space 2} .1143954{col 37}{space 1}    1.87{col 46}{space 3}0.062{col 54}{space 4}-.0103949{col 67}{space 3} .4380269
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~l {c |}{col 14}{res}{space 2}  .389958{col 26}{space 2} .1144482{col 37}{space 1}    3.41{col 46}{space 3}0.001{col 54}{space 4} .1656437{col 67}{space 3} .6142724
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~l {c |}{col 14}{res}{space 2}-.0231602{col 26}{space 2} .1041278{col 37}{space 1}   -0.22{col 46}{space 3}0.824{col 54}{space 4} -.227247{col 67}{space 3} .1809266
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~y {c |}{col 14}{res}{space 2} .7191527{col 26}{space 2} .1270947{col 37}{space 1}    5.66{col 46}{space 3}0.000{col 54}{space 4} .4700518{col 67}{space 3} .9682537
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~y {c |}{col 14}{res}{space 2}-.0657753{col 26}{space 2} .1121867{col 37}{space 1}   -0.59{col 46}{space 3}0.558{col 54}{space 4}-.2856571{col 67}{space 3} .1541065
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~e {c |}{col 14}{res}{space 2} .4531286{col 26}{space 2}  .112368{col 37}{space 1}    4.03{col 46}{space 3}0.000{col 54}{space 4} .2328914{col 67}{space 3} .6733657
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~e {c |}{col 14}{res}{space 2}-.2351948{col 26}{space 2}  .094304{col 37}{space 1}   -2.49{col 46}{space 3}0.013{col 54}{space 4}-.4200272{col 67}{space 3}-.0503625
{txt}{space 12} {c |}
{space 6}female {c |}{col 14}{res}{space 2} .1184107{col 26}{space 2} .1063667{col 37}{space 1}    1.11{col 46}{space 3}0.266{col 54}{space 4}-.0900641{col 67}{space 3} .3268856
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0096834{col 26}{space 2} .0046737{col 37}{space 1}    2.07{col 46}{space 3}0.038{col 54}{space 4}  .000523{col 67}{space 3} .0188437
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0223141{col 26}{space 2} .0365504{col 37}{space 1}   -0.61{col 46}{space 3}0.542{col 54}{space 4}-.0939516{col 67}{space 3} .0493233
{txt}{space 8}room {c |}{col 14}{res}{space 2}-.0812195{col 26}{space 2} .0332904{col 37}{space 1}   -2.44{col 46}{space 3}0.015{col 54}{space 4}-.1464676{col 67}{space 3}-.0159715
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .1762306{col 26}{space 2} .1757406{col 37}{space 1}    1.00{col 46}{space 3}0.316{col 54}{space 4}-.1682146{col 67}{space 3} .5206759
{txt}{space 2}darabmixed {c |}{col 14}{res}{space 2} .2549083{col 26}{space 2} .1361193{col 37}{space 1}    1.87{col 46}{space 3}0.061{col 54}{space 4}-.0118807{col 67}{space 3} .5216973
{txt}{space 3}religious {c |}{col 14}{res}{space 2}-.3883944{col 26}{space 2} .0909829{col 37}{space 1}   -4.27{col 46}{space 3}0.000{col 54}{space 4}-.5667177{col 67}{space 3}-.2100711
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-1.700897{col 26}{space 2} .3625815{col 37}{space 1}   -4.69{col 46}{space 3}0.000{col 54}{space 4}-2.411543{col 67}{space 3}-.9902499
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. logit bias c.pov1##c.biasthreat_labor c.pov1##c.biasthreat_fiscal c.pov1##c.biasthreat_security c.pov1##c.biasthreat_culture female age education vacation unemployed darabmixed religious, cluster(dst)

{txt}note: pov1 omitted because of collinearity
note: pov1 omitted because of collinearity
note: pov1 omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1333.2833}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1198.5705}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1192.4852}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1192.4641}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1192.4641}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      2370
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}    279.64
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-1192.4641{txt}{col 51}Pseudo R2{col 67}= {res}    0.1056

{txt}{ralign 78:(Std. Err. adjusted for {res:150} clusters in dst)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        bias{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}pov1 {c |}{col 14}{res}{space 2}-.0801379{col 26}{space 2} .1088145{col 37}{space 1}   -0.74{col 46}{space 3}0.461{col 54}{space 4}-.2934104{col 67}{space 3} .1331346
{txt}biasthreat~r {c |}{col 14}{res}{space 2} .5384684{col 26}{space 2} .1246529{col 37}{space 1}    4.32{col 46}{space 3}0.000{col 54}{space 4} .2941532{col 67}{space 3} .7827837
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~r {c |}{col 14}{res}{space 2} .2239598{col 26}{space 2} .1164404{col 37}{space 1}    1.92{col 46}{space 3}0.054{col 54}{space 4}-.0042592{col 67}{space 3} .4521788
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~l {c |}{col 14}{res}{space 2} .4044022{col 26}{space 2} .1160633{col 37}{space 1}    3.48{col 46}{space 3}0.000{col 54}{space 4} .1769223{col 67}{space 3} .6318821
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~l {c |}{col 14}{res}{space 2}-.0254172{col 26}{space 2} .1070177{col 37}{space 1}   -0.24{col 46}{space 3}0.812{col 54}{space 4}-.2351681{col 67}{space 3} .1843337
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~y {c |}{col 14}{res}{space 2} .7127964{col 26}{space 2} .1288163{col 37}{space 1}    5.53{col 46}{space 3}0.000{col 54}{space 4} .4603212{col 67}{space 3} .9652716
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~y {c |}{col 14}{res}{space 2}-.0477286{col 26}{space 2} .1147632{col 37}{space 1}   -0.42{col 46}{space 3}0.677{col 54}{space 4}-.2726605{col 67}{space 3} .1772032
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~e {c |}{col 14}{res}{space 2} .4633513{col 26}{space 2} .1135702{col 37}{space 1}    4.08{col 46}{space 3}0.000{col 54}{space 4} .2407577{col 67}{space 3} .6859449
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~e {c |}{col 14}{res}{space 2}-.2453708{col 26}{space 2} .0953238{col 37}{space 1}   -2.57{col 46}{space 3}0.010{col 54}{space 4} -.432202{col 67}{space 3}-.0585396
{txt}{space 12} {c |}
{space 6}female {c |}{col 14}{res}{space 2} .1240662{col 26}{space 2} .1051139{col 37}{space 1}    1.18{col 46}{space 3}0.238{col 54}{space 4}-.0819532{col 67}{space 3} .3300856
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0081771{col 26}{space 2} .0046645{col 37}{space 1}    1.75{col 46}{space 3}0.080{col 54}{space 4}-.0009651{col 67}{space 3} .0173194
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0383719{col 26}{space 2}  .038868{col 37}{space 1}   -0.99{col 46}{space 3}0.324{col 54}{space 4}-.1145518{col 67}{space 3}  .037808
{txt}{space 4}vacation {c |}{col 14}{res}{space 2} .0857425{col 26}{space 2} .1033762{col 37}{space 1}    0.83{col 46}{space 3}0.407{col 54}{space 4}-.1168711{col 67}{space 3} .2883561
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .2196656{col 26}{space 2} .1743859{col 37}{space 1}    1.26{col 46}{space 3}0.208{col 54}{space 4}-.1221246{col 67}{space 3} .5614557
{txt}{space 2}darabmixed {c |}{col 14}{res}{space 2} .2873276{col 26}{space 2}   .13805{col 37}{space 1}    2.08{col 46}{space 3}0.037{col 54}{space 4} .0167545{col 67}{space 3} .5579007
{txt}{space 3}religious {c |}{col 14}{res}{space 2}-.3951881{col 26}{space 2} .0897291{col 37}{space 1}   -4.40{col 46}{space 3}0.000{col 54}{space 4}-.5710538{col 67}{space 3}-.2193223
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} -2.06239{col 26}{space 2} .3802992{col 37}{space 1}   -5.42{col 46}{space 3}0.000{col 54}{space 4}-2.807763{col 67}{space 3}-1.317017
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. 
. 
. logit bias d1-d148 c.pov1##c.biasthreat_labor c.pov1##c.biasthreat_fiscal c.pov1##c.biasthreat_security c.pov1##c.biasthreat_culture female age education sufficient unemployed darabmixed religious, cluster(dst)

{txt}note: d1 != 0 predicts failure perfectly
      d1 dropped and 12 obs not used

note: d22 != 0 predicts failure perfectly
      d22 dropped and 15 obs not used

note: d28 != 0 predicts failure perfectly
      d28 dropped and 18 obs not used

note: d35 != 0 predicts failure perfectly
      d35 dropped and 15 obs not used

note: d40 != 0 predicts failure perfectly
      d40 dropped and 14 obs not used

note: d47 != 0 predicts failure perfectly
      d47 dropped and 12 obs not used

note: d131 != 0 predicts failure perfectly
      d131 dropped and 13 obs not used

note: pov1 omitted because of collinearity
note: pov1 omitted because of collinearity
note: pov1 omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1260.0949}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1040.4455}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1023.9712}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1023.7717}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1023.7713}  
Iteration 5:{space 3}log pseudolikelihood = {res:-1023.7713}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      2212
{txt}{col 51}{help j_robustsingular##|_new:Wald chi2(14)}{col 67}=          {res}.
{txt}{col 51}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-1023.7713{txt}{col 51}Pseudo R2{col 67}= {res}    0.1875

{txt}{ralign 78:(Std. Err. adjusted for {res:143} clusters in dst)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        bias{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}d1 {c |}{col 14}{res}  (omitted)
{txt}{space 10}d2 {c |}{col 14}{res}{space 2}  67.5147{col 26}{space 2}  2.67026{col 37}{space 1}   25.28{col 46}{space 3}0.000{col 54}{space 4} 62.28108{col 67}{space 3} 72.74831
{txt}{space 10}d3 {c |}{col 14}{res}{space 2} 7.203521{col 26}{space 2} .3167401{col 37}{space 1}   22.74{col 46}{space 3}0.000{col 54}{space 4} 6.582722{col 67}{space 3} 7.824321
{txt}{space 10}d4 {c |}{col 14}{res}{space 2} 72.86364{col 26}{space 2} 2.770188{col 37}{space 1}   26.30{col 46}{space 3}0.000{col 54}{space 4} 67.43417{col 67}{space 3} 78.29311
{txt}{space 10}d5 {c |}{col 14}{res}{space 2} 31.00784{col 26}{space 2} 1.187161{col 37}{space 1}   26.12{col 46}{space 3}0.000{col 54}{space 4} 28.68104{col 67}{space 3} 33.33463
{txt}{space 10}d6 {c |}{col 14}{res}{space 2} 51.39814{col 26}{space 2} 1.936069{col 37}{space 1}   26.55{col 46}{space 3}0.000{col 54}{space 4} 47.60351{col 67}{space 3} 55.19276
{txt}{space 10}d7 {c |}{col 14}{res}{space 2} 25.85033{col 26}{space 2} 1.005774{col 37}{space 1}   25.70{col 46}{space 3}0.000{col 54}{space 4} 23.87905{col 67}{space 3} 27.82161
{txt}{space 10}d8 {c |}{col 14}{res}{space 2} 48.44313{col 26}{space 2} 1.850447{col 37}{space 1}   26.18{col 46}{space 3}0.000{col 54}{space 4} 44.81633{col 67}{space 3} 52.06994
{txt}{space 10}d9 {c |}{col 14}{res}{space 2} 62.21918{col 26}{space 2} 2.326006{col 37}{space 1}   26.75{col 46}{space 3}0.000{col 54}{space 4} 57.66029{col 67}{space 3} 66.77807
{txt}{space 9}d10 {c |}{col 14}{res}{space 2} 64.09217{col 26}{space 2} 2.350374{col 37}{space 1}   27.27{col 46}{space 3}0.000{col 54}{space 4} 59.48552{col 67}{space 3} 68.69881
{txt}{space 9}d11 {c |}{col 14}{res}{space 2} 65.30186{col 26}{space 2} 2.368717{col 37}{space 1}   27.57{col 46}{space 3}0.000{col 54}{space 4} 60.65926{col 67}{space 3} 69.94446
{txt}{space 9}d12 {c |}{col 14}{res}{space 2} 41.45008{col 26}{space 2} 1.523473{col 37}{space 1}   27.21{col 46}{space 3}0.000{col 54}{space 4} 38.46413{col 67}{space 3} 44.43603
{txt}{space 9}d13 {c |}{col 14}{res}{space 2} 11.50202{col 26}{space 2} .4004158{col 37}{space 1}   28.73{col 46}{space 3}0.000{col 54}{space 4} 10.71722{col 67}{space 3} 12.28683
{txt}{space 9}d14 {c |}{col 14}{res}{space 2} 41.71405{col 26}{space 2} 1.581856{col 37}{space 1}   26.37{col 46}{space 3}0.000{col 54}{space 4} 38.61367{col 67}{space 3} 44.81444
{txt}{space 9}d15 {c |}{col 14}{res}{space 2} 26.40291{col 26}{space 2} 1.027079{col 37}{space 1}   25.71{col 46}{space 3}0.000{col 54}{space 4} 24.38987{col 67}{space 3} 28.41595
{txt}{space 9}d16 {c |}{col 14}{res}{space 2} 25.30399{col 26}{space 2} 1.039636{col 37}{space 1}   24.34{col 46}{space 3}0.000{col 54}{space 4} 23.26634{col 67}{space 3} 27.34164
{txt}{space 9}d17 {c |}{col 14}{res}{space 2} 24.49135{col 26}{space 2} 1.008066{col 37}{space 1}   24.30{col 46}{space 3}0.000{col 54}{space 4} 22.51558{col 67}{space 3} 26.46712
{txt}{space 9}d18 {c |}{col 14}{res}{space 2} 67.37374{col 26}{space 2} 2.655879{col 37}{space 1}   25.37{col 46}{space 3}0.000{col 54}{space 4} 62.16831{col 67}{space 3} 72.57917
{txt}{space 9}d19 {c |}{col 14}{res}{space 2} 46.66214{col 26}{space 2} 1.780653{col 37}{space 1}   26.21{col 46}{space 3}0.000{col 54}{space 4} 43.17213{col 67}{space 3} 50.15216
{txt}{space 9}d20 {c |}{col 14}{res}{space 2} 26.63933{col 26}{space 2} 1.019198{col 37}{space 1}   26.14{col 46}{space 3}0.000{col 54}{space 4} 24.64174{col 67}{space 3} 28.63693
{txt}{space 9}d21 {c |}{col 14}{res}{space 2} 43.84835{col 26}{space 2} 1.610191{col 37}{space 1}   27.23{col 46}{space 3}0.000{col 54}{space 4} 40.69243{col 67}{space 3} 47.00427
{txt}{space 9}d22 {c |}{col 14}{res}  (omitted)
{txt}{space 9}d23 {c |}{col 14}{res}{space 2} 2.845755{col 26}{space 2} .1972051{col 37}{space 1}   14.43{col 46}{space 3}0.000{col 54}{space 4}  2.45924{col 67}{space 3}  3.23227
{txt}{space 9}d24 {c |}{col 14}{res}{space 2} 62.30465{col 26}{space 2} 2.297682{col 37}{space 1}   27.12{col 46}{space 3}0.000{col 54}{space 4} 57.80128{col 67}{space 3} 66.80803
{txt}{space 9}d25 {c |}{col 14}{res}{space 2} 15.29369{col 26}{space 2} .7841205{col 37}{space 1}   19.50{col 46}{space 3}0.000{col 54}{space 4} 13.75684{col 67}{space 3} 16.83054
{txt}{space 9}d26 {c |}{col 14}{res}{space 2} 9.516552{col 26}{space 2} .4891348{col 37}{space 1}   19.46{col 46}{space 3}0.000{col 54}{space 4} 8.557866{col 67}{space 3} 10.47524
{txt}{space 9}d27 {c |}{col 14}{res}{space 2} 28.36945{col 26}{space 2} 1.145079{col 37}{space 1}   24.78{col 46}{space 3}0.000{col 54}{space 4} 26.12514{col 67}{space 3} 30.61377
{txt}{space 9}d28 {c |}{col 14}{res}  (omitted)
{txt}{space 9}d29 {c |}{col 14}{res}{space 2} 30.71753{col 26}{space 2} 1.141599{col 37}{space 1}   26.91{col 46}{space 3}0.000{col 54}{space 4} 28.48004{col 67}{space 3} 32.95503
{txt}{space 9}d30 {c |}{col 14}{res}{space 2} 12.43343{col 26}{space 2} .3916165{col 37}{space 1}   31.75{col 46}{space 3}0.000{col 54}{space 4} 11.66587{col 67}{space 3} 13.20098
{txt}{space 9}d31 {c |}{col 14}{res}{space 2} 33.13709{col 26}{space 2} 1.279881{col 37}{space 1}   25.89{col 46}{space 3}0.000{col 54}{space 4} 30.62857{col 67}{space 3} 35.64561
{txt}{space 9}d32 {c |}{col 14}{res}{space 2} 23.44014{col 26}{space 2} .8262814{col 37}{space 1}   28.37{col 46}{space 3}0.000{col 54}{space 4} 21.82065{col 67}{space 3} 25.05962
{txt}{space 9}d33 {c |}{col 14}{res}{space 2} 36.70875{col 26}{space 2} 1.399162{col 37}{space 1}   26.24{col 46}{space 3}0.000{col 54}{space 4} 33.96644{col 67}{space 3} 39.45106
{txt}{space 9}d34 {c |}{col 14}{res}{space 2} 30.32398{col 26}{space 2} 1.146072{col 37}{space 1}   26.46{col 46}{space 3}0.000{col 54}{space 4} 28.07772{col 67}{space 3} 32.57024
{txt}{space 9}d35 {c |}{col 14}{res}  (omitted)
{txt}{space 9}d36 {c |}{col 14}{res}{space 2} 26.44608{col 26}{space 2} 1.048861{col 37}{space 1}   25.21{col 46}{space 3}0.000{col 54}{space 4} 24.39035{col 67}{space 3} 28.50182
{txt}{space 9}d37 {c |}{col 14}{res}{space 2} 25.66055{col 26}{space 2} 1.071632{col 37}{space 1}   23.95{col 46}{space 3}0.000{col 54}{space 4} 23.56019{col 67}{space 3} 27.76092
{txt}{space 9}d38 {c |}{col 14}{res}{space 2} 38.98712{col 26}{space 2} 1.529234{col 37}{space 1}   25.49{col 46}{space 3}0.000{col 54}{space 4} 35.98988{col 67}{space 3} 41.98436
{txt}{space 9}d39 {c |}{col 14}{res}{space 2}  55.5034{col 26}{space 2} 2.135469{col 37}{space 1}   25.99{col 46}{space 3}0.000{col 54}{space 4} 51.31796{col 67}{space 3} 59.68884
{txt}{space 9}d40 {c |}{col 14}{res}  (omitted)
{txt}{space 9}d41 {c |}{col 14}{res}{space 2} 62.65928{col 26}{space 2}  2.34772{col 37}{space 1}   26.69{col 46}{space 3}0.000{col 54}{space 4} 58.05784{col 67}{space 3} 67.26073
{txt}{space 9}d42 {c |}{col 14}{res}{space 2}  20.9111{col 26}{space 2} .6886079{col 37}{space 1}   30.37{col 46}{space 3}0.000{col 54}{space 4} 19.56145{col 67}{space 3} 22.26075
{txt}{space 9}d43 {c |}{col 14}{res}{space 2} 43.53861{col 26}{space 2} 1.662315{col 37}{space 1}   26.19{col 46}{space 3}0.000{col 54}{space 4} 40.28053{col 67}{space 3} 46.79668
{txt}{space 9}d44 {c |}{col 14}{res}{space 2} 59.31378{col 26}{space 2} 2.202987{col 37}{space 1}   26.92{col 46}{space 3}0.000{col 54}{space 4} 54.99601{col 67}{space 3} 63.63156
{txt}{space 9}d45 {c |}{col 14}{res}{space 2} 44.00213{col 26}{space 2} 1.568882{col 37}{space 1}   28.05{col 46}{space 3}0.000{col 54}{space 4} 40.92718{col 67}{space 3} 47.07709
{txt}{space 9}d46 {c |}{col 14}{res}{space 2} 12.34661{col 26}{space 2} .4980684{col 37}{space 1}   24.79{col 46}{space 3}0.000{col 54}{space 4} 11.37041{col 67}{space 3}  13.3228
{txt}{space 9}d47 {c |}{col 14}{res}  (omitted)
{txt}{space 9}d48 {c |}{col 14}{res}{space 2} 38.48333{col 26}{space 2} 1.411306{col 37}{space 1}   27.27{col 46}{space 3}0.000{col 54}{space 4} 35.71722{col 67}{space 3} 41.24944
{txt}{space 9}d49 {c |}{col 14}{res}{space 2} 39.44814{col 26}{space 2} 1.447539{col 37}{space 1}   27.25{col 46}{space 3}0.000{col 54}{space 4} 36.61102{col 67}{space 3} 42.28527
{txt}{space 9}d50 {c |}{col 14}{res}{space 2} 25.54295{col 26}{space 2} .9549345{col 37}{space 1}   26.75{col 46}{space 3}0.000{col 54}{space 4} 23.67131{col 67}{space 3} 27.41458
{txt}{space 9}d51 {c |}{col 14}{res}{space 2} 57.81057{col 26}{space 2} 2.142782{col 37}{space 1}   26.98{col 46}{space 3}0.000{col 54}{space 4}  53.6108{col 67}{space 3} 62.01035
{txt}{space 9}d52 {c |}{col 14}{res}{space 2} 31.80461{col 26}{space 2} 1.170388{col 37}{space 1}   27.17{col 46}{space 3}0.000{col 54}{space 4} 29.51069{col 67}{space 3} 34.09853
{txt}{space 9}d53 {c |}{col 14}{res}{space 2}-4.217713{col 26}{space 2} .2107668{col 37}{space 1}  -20.01{col 46}{space 3}0.000{col 54}{space 4}-4.630809{col 67}{space 3}-3.804618
{txt}{space 9}d54 {c |}{col 14}{res}{space 2} 12.10109{col 26}{space 2} .4798295{col 37}{space 1}   25.22{col 46}{space 3}0.000{col 54}{space 4} 11.16064{col 67}{space 3} 13.04153
{txt}{space 9}d55 {c |}{col 14}{res}{space 2} 9.846784{col 26}{space 2} .2941911{col 37}{space 1}   33.47{col 46}{space 3}0.000{col 54}{space 4}  9.27018{col 67}{space 3} 10.42339
{txt}{space 9}d56 {c |}{col 14}{res}{space 2} 9.869054{col 26}{space 2} .3602669{col 37}{space 1}   27.39{col 46}{space 3}0.000{col 54}{space 4} 9.162944{col 67}{space 3} 10.57516
{txt}{space 9}d57 {c |}{col 14}{res}{space 2}  .849342{col 26}{space 2} .1071513{col 37}{space 1}    7.93{col 46}{space 3}0.000{col 54}{space 4} .6393294{col 67}{space 3} 1.059355
{txt}{space 9}d58 {c |}{col 14}{res}{space 2} 1.256794{col 26}{space 2} .1073171{col 37}{space 1}   11.71{col 46}{space 3}0.000{col 54}{space 4} 1.046456{col 67}{space 3} 1.467132
{txt}{space 9}d59 {c |}{col 14}{res}{space 2}-7.354146{col 26}{space 2} .2932793{col 37}{space 1}  -25.08{col 46}{space 3}0.000{col 54}{space 4}-7.928962{col 67}{space 3}-6.779329
{txt}{space 9}d60 {c |}{col 14}{res}{space 2} -3.08193{col 26}{space 2} .1663928{col 37}{space 1}  -18.52{col 46}{space 3}0.000{col 54}{space 4}-3.408054{col 67}{space 3}-2.755806
{txt}{space 9}d61 {c |}{col 14}{res}{space 2} -2.90809{col 26}{space 2} .1412829{col 37}{space 1}  -20.58{col 46}{space 3}0.000{col 54}{space 4}   -3.185{col 67}{space 3}-2.631181
{txt}{space 9}d62 {c |}{col 14}{res}{space 2}-3.502662{col 26}{space 2} .1548086{col 37}{space 1}  -22.63{col 46}{space 3}0.000{col 54}{space 4}-3.806081{col 67}{space 3}-3.199242
{txt}{space 9}d63 {c |}{col 14}{res}{space 2} 3.815371{col 26}{space 2} .1548745{col 37}{space 1}   24.64{col 46}{space 3}0.000{col 54}{space 4} 3.511822{col 67}{space 3} 4.118919
{txt}{space 9}d64 {c |}{col 14}{res}{space 2}  34.8093{col 26}{space 2}  1.24568{col 37}{space 1}   27.94{col 46}{space 3}0.000{col 54}{space 4} 32.36782{col 67}{space 3} 37.25079
{txt}{space 9}d65 {c |}{col 14}{res}{space 2} 5.214596{col 26}{space 2} .1802359{col 37}{space 1}   28.93{col 46}{space 3}0.000{col 54}{space 4}  4.86134{col 67}{space 3} 5.567852
{txt}{space 9}d66 {c |}{col 14}{res}{space 2} 9.384168{col 26}{space 2} .2770773{col 37}{space 1}   33.87{col 46}{space 3}0.000{col 54}{space 4} 8.841106{col 67}{space 3} 9.927229
{txt}{space 9}d67 {c |}{col 14}{res}{space 2} 5.500986{col 26}{space 2}  .175101{col 37}{space 1}   31.42{col 46}{space 3}0.000{col 54}{space 4} 5.157794{col 67}{space 3} 5.844177
{txt}{space 9}d68 {c |}{col 14}{res}{space 2} 6.152813{col 26}{space 2} .1636787{col 37}{space 1}   37.59{col 46}{space 3}0.000{col 54}{space 4} 5.832009{col 67}{space 3} 6.473617
{txt}{space 9}d69 {c |}{col 14}{res}{space 2} 30.13245{col 26}{space 2}  1.08172{col 37}{space 1}   27.86{col 46}{space 3}0.000{col 54}{space 4} 28.01232{col 67}{space 3} 32.25258
{txt}{space 9}d70 {c |}{col 14}{res}{space 2} 6.823602{col 26}{space 2} .2515026{col 37}{space 1}   27.13{col 46}{space 3}0.000{col 54}{space 4} 6.330666{col 67}{space 3} 7.316538
{txt}{space 9}d71 {c |}{col 14}{res}{space 2} 7.334032{col 26}{space 2}  .199466{col 37}{space 1}   36.77{col 46}{space 3}0.000{col 54}{space 4} 6.943086{col 67}{space 3} 7.724978
{txt}{space 9}d72 {c |}{col 14}{res}{space 2} 6.888832{col 26}{space 2} .2225892{col 37}{space 1}   30.95{col 46}{space 3}0.000{col 54}{space 4} 6.452565{col 67}{space 3} 7.325099
{txt}{space 9}d73 {c |}{col 14}{res}{space 2} 41.69382{col 26}{space 2}  1.52711{col 37}{space 1}   27.30{col 46}{space 3}0.000{col 54}{space 4} 38.70074{col 67}{space 3}  44.6869
{txt}{space 9}d74 {c |}{col 14}{res}{space 2}-5.187365{col 26}{space 2} .3206809{col 37}{space 1}  -16.18{col 46}{space 3}0.000{col 54}{space 4}-5.815888{col 67}{space 3}-4.558842
{txt}{space 9}d75 {c |}{col 14}{res}{space 2} 2.494389{col 26}{space 2} .0832406{col 37}{space 1}   29.97{col 46}{space 3}0.000{col 54}{space 4} 2.331241{col 67}{space 3} 2.657538
{txt}{space 9}d76 {c |}{col 14}{res}{space 2} 27.20733{col 26}{space 2} .9804237{col 37}{space 1}   27.75{col 46}{space 3}0.000{col 54}{space 4} 25.28574{col 67}{space 3} 29.12893
{txt}{space 9}d77 {c |}{col 14}{res}{space 2} 16.04637{col 26}{space 2} .5380095{col 37}{space 1}   29.83{col 46}{space 3}0.000{col 54}{space 4} 14.99189{col 67}{space 3} 17.10085
{txt}{space 9}d78 {c |}{col 14}{res}{space 2} 16.08445{col 26}{space 2} .5240023{col 37}{space 1}   30.70{col 46}{space 3}0.000{col 54}{space 4} 15.05743{col 67}{space 3} 17.11148
{txt}{space 9}d79 {c |}{col 14}{res}{space 2} 9.273479{col 26}{space 2} .2944656{col 37}{space 1}   31.49{col 46}{space 3}0.000{col 54}{space 4} 8.696337{col 67}{space 3} 9.850621
{txt}{space 9}d80 {c |}{col 14}{res}{space 2} .9641235{col 26}{space 2} .0909071{col 37}{space 1}   10.61{col 46}{space 3}0.000{col 54}{space 4} .7859489{col 67}{space 3} 1.142298
{txt}{space 9}d81 {c |}{col 14}{res}{space 2}  1.04852{col 26}{space 2} .0841659{col 37}{space 1}   12.46{col 46}{space 3}0.000{col 54}{space 4}  .883558{col 67}{space 3} 1.213482
{txt}{space 9}d82 {c |}{col 14}{res}{space 2} 12.51817{col 26}{space 2} .4322531{col 37}{space 1}   28.96{col 46}{space 3}0.000{col 54}{space 4} 11.67097{col 67}{space 3} 13.36537
{txt}{space 9}d83 {c |}{col 14}{res}{space 2} 12.00763{col 26}{space 2} .4305894{col 37}{space 1}   27.89{col 46}{space 3}0.000{col 54}{space 4} 11.16369{col 67}{space 3} 12.85157
{txt}{space 9}d84 {c |}{col 14}{res}{space 2} 12.45949{col 26}{space 2} .4302726{col 37}{space 1}   28.96{col 46}{space 3}0.000{col 54}{space 4} 11.61617{col 67}{space 3} 13.30281
{txt}{space 9}d85 {c |}{col 14}{res}{space 2} 12.44297{col 26}{space 2} .4466943{col 37}{space 1}   27.86{col 46}{space 3}0.000{col 54}{space 4} 11.56746{col 67}{space 3} 13.31847
{txt}{space 9}d86 {c |}{col 14}{res}{space 2} 22.45678{col 26}{space 2} .7887404{col 37}{space 1}   28.47{col 46}{space 3}0.000{col 54}{space 4} 20.91088{col 67}{space 3} 24.00269
{txt}{space 9}d87 {c |}{col 14}{res}{space 2}-9.306502{col 26}{space 2} .4300312{col 37}{space 1}  -21.64{col 46}{space 3}0.000{col 54}{space 4}-10.14935{col 67}{space 3}-8.463657
{txt}{space 9}d88 {c |}{col 14}{res}{space 2}-1.575228{col 26}{space 2} .1041477{col 37}{space 1}  -15.12{col 46}{space 3}0.000{col 54}{space 4}-1.779354{col 67}{space 3}-1.371102
{txt}{space 9}d89 {c |}{col 14}{res}{space 2}-1.591994{col 26}{space 2} .0972382{col 37}{space 1}  -16.37{col 46}{space 3}0.000{col 54}{space 4}-1.782577{col 67}{space 3} -1.40141
{txt}{space 9}d90 {c |}{col 14}{res}{space 2}-.8567951{col 26}{space 2} .1123601{col 37}{space 1}   -7.63{col 46}{space 3}0.000{col 54}{space 4}-1.077017{col 67}{space 3}-.6365734
{txt}{space 9}d91 {c |}{col 14}{res}{space 2} 20.74687{col 26}{space 2} .7380806{col 37}{space 1}   28.11{col 46}{space 3}0.000{col 54}{space 4} 19.30026{col 67}{space 3} 22.19348
{txt}{space 9}d92 {c |}{col 14}{res}{space 2}  20.1732{col 26}{space 2} .7579742{col 37}{space 1}   26.61{col 46}{space 3}0.000{col 54}{space 4} 18.68759{col 67}{space 3}  21.6588
{txt}{space 9}d93 {c |}{col 14}{res}{space 2} 2.346437{col 26}{space 2} .0824192{col 37}{space 1}   28.47{col 46}{space 3}0.000{col 54}{space 4} 2.184899{col 67}{space 3} 2.507976
{txt}{space 9}d94 {c |}{col 14}{res}{space 2} 26.04213{col 26}{space 2} .9528559{col 37}{space 1}   27.33{col 46}{space 3}0.000{col 54}{space 4} 24.17457{col 67}{space 3} 27.90969
{txt}{space 9}d95 {c |}{col 14}{res}{space 2} 28.95768{col 26}{space 2} 1.020468{col 37}{space 1}   28.38{col 46}{space 3}0.000{col 54}{space 4}  26.9576{col 67}{space 3} 30.95776
{txt}{space 9}d96 {c |}{col 14}{res}{space 2}-9.123432{col 26}{space 2} .4390269{col 37}{space 1}  -20.78{col 46}{space 3}0.000{col 54}{space 4}-9.983909{col 67}{space 3}-8.262955
{txt}{space 9}d97 {c |}{col 14}{res}{space 2}-.4776852{col 26}{space 2} .1175785{col 37}{space 1}   -4.06{col 46}{space 3}0.000{col 54}{space 4}-.7081347{col 67}{space 3}-.2472357
{txt}{space 9}d98 {c |}{col 14}{res}{space 2} 19.62375{col 26}{space 2} .7899679{col 37}{space 1}   24.84{col 46}{space 3}0.000{col 54}{space 4} 18.07544{col 67}{space 3} 21.17206
{txt}{space 9}d99 {c |}{col 14}{res}{space 2}  7.06366{col 26}{space 2} .2657843{col 37}{space 1}   26.58{col 46}{space 3}0.000{col 54}{space 4} 6.542732{col 67}{space 3} 7.584587
{txt}{space 8}d100 {c |}{col 14}{res}{space 2} 13.42336{col 26}{space 2} .5851795{col 37}{space 1}   22.94{col 46}{space 3}0.000{col 54}{space 4} 12.27643{col 67}{space 3} 14.57029
{txt}{space 8}d101 {c |}{col 14}{res}{space 2} 18.93757{col 26}{space 2} .7282082{col 37}{space 1}   26.01{col 46}{space 3}0.000{col 54}{space 4} 17.51031{col 67}{space 3} 20.36483
{txt}{space 8}d102 {c |}{col 14}{res}{space 2} 17.46863{col 26}{space 2} .6658437{col 37}{space 1}   26.24{col 46}{space 3}0.000{col 54}{space 4}  16.1636{col 67}{space 3} 18.77366
{txt}{space 8}d103 {c |}{col 14}{res}{space 2} 16.35696{col 26}{space 2} .6150478{col 37}{space 1}   26.59{col 46}{space 3}0.000{col 54}{space 4} 15.15149{col 67}{space 3} 17.56244
{txt}{space 8}d104 {c |}{col 14}{res}{space 2} 1.445949{col 26}{space 2} .0728756{col 37}{space 1}   19.84{col 46}{space 3}0.000{col 54}{space 4} 1.303115{col 67}{space 3} 1.588782
{txt}{space 8}d105 {c |}{col 14}{res}{space 2} 11.13862{col 26}{space 2} .3782045{col 37}{space 1}   29.45{col 46}{space 3}0.000{col 54}{space 4} 10.39736{col 67}{space 3} 11.87989
{txt}{space 8}d106 {c |}{col 14}{res}{space 2}-.3643874{col 26}{space 2}  .177559{col 37}{space 1}   -2.05{col 46}{space 3}0.040{col 54}{space 4}-.7123966{col 67}{space 3}-.0163781
{txt}{space 8}d107 {c |}{col 14}{res}{space 2} .6333232{col 26}{space 2} .1258773{col 37}{space 1}    5.03{col 46}{space 3}0.000{col 54}{space 4} .3866082{col 67}{space 3} .8800382
{txt}{space 8}d108 {c |}{col 14}{res}{space 2}-2.750544{col 26}{space 2} .1630421{col 37}{space 1}  -16.87{col 46}{space 3}0.000{col 54}{space 4}  -3.0701{col 67}{space 3}-2.430987
{txt}{space 8}d109 {c |}{col 14}{res}{space 2}-2.970085{col 26}{space 2} .1986272{col 37}{space 1}  -14.95{col 46}{space 3}0.000{col 54}{space 4}-3.359387{col 67}{space 3}-2.580783
{txt}{space 8}d110 {c |}{col 14}{res}{space 2} 3.638046{col 26}{space 2} .1055569{col 37}{space 1}   34.47{col 46}{space 3}0.000{col 54}{space 4} 3.431159{col 67}{space 3} 3.844934
{txt}{space 8}d111 {c |}{col 14}{res}{space 2}  3.83368{col 26}{space 2} .1271481{col 37}{space 1}   30.15{col 46}{space 3}0.000{col 54}{space 4} 3.584474{col 67}{space 3} 4.082885
{txt}{space 8}d112 {c |}{col 14}{res}{space 2} 3.771062{col 26}{space 2} .0988076{col 37}{space 1}   38.17{col 46}{space 3}0.000{col 54}{space 4} 3.577402{col 67}{space 3} 3.964721
{txt}{space 8}d113 {c |}{col 14}{res}{space 2}-7.138619{col 26}{space 2} .2744137{col 37}{space 1}  -26.01{col 46}{space 3}0.000{col 54}{space 4} -7.67646{col 67}{space 3}-6.600778
{txt}{space 8}d114 {c |}{col 14}{res}{space 2}-2.898099{col 26}{space 2} .2421827{col 37}{space 1}  -11.97{col 46}{space 3}0.000{col 54}{space 4}-3.372769{col 67}{space 3} -2.42343
{txt}{space 8}d115 {c |}{col 14}{res}{space 2}-3.181247{col 26}{space 2} .2269738{col 37}{space 1}  -14.02{col 46}{space 3}0.000{col 54}{space 4}-3.626107{col 67}{space 3}-2.736386
{txt}{space 8}d116 {c |}{col 14}{res}{space 2}-4.090462{col 26}{space 2} .2189172{col 37}{space 1}  -18.68{col 46}{space 3}0.000{col 54}{space 4}-4.519532{col 67}{space 3}-3.661392
{txt}{space 8}d117 {c |}{col 14}{res}{space 2} -3.79689{col 26}{space 2} .2508614{col 37}{space 1}  -15.14{col 46}{space 3}0.000{col 54}{space 4}-4.288569{col 67}{space 3}-3.305211
{txt}{space 8}d118 {c |}{col 14}{res}{space 2}-4.852872{col 26}{space 2}   .22935{col 37}{space 1}  -21.16{col 46}{space 3}0.000{col 54}{space 4} -5.30239{col 67}{space 3}-4.403354
{txt}{space 8}d119 {c |}{col 14}{res}{space 2}-.0987428{col 26}{space 2} .0916712{col 37}{space 1}   -1.08{col 46}{space 3}0.281{col 54}{space 4}-.2784152{col 67}{space 3} .0809295
{txt}{space 8}d120 {c |}{col 14}{res}{space 2}  2.13606{col 26}{space 2} .1051702{col 37}{space 1}   20.31{col 46}{space 3}0.000{col 54}{space 4}  1.92993{col 67}{space 3}  2.34219
{txt}{space 8}d121 {c |}{col 14}{res}{space 2} 7.690809{col 26}{space 2} .2719984{col 37}{space 1}   28.28{col 46}{space 3}0.000{col 54}{space 4} 7.157702{col 67}{space 3} 8.223916
{txt}{space 8}d122 {c |}{col 14}{res}{space 2} 6.298377{col 26}{space 2} .2760895{col 37}{space 1}   22.81{col 46}{space 3}0.000{col 54}{space 4} 5.757252{col 67}{space 3} 6.839502
{txt}{space 8}d123 {c |}{col 14}{res}{space 2} 1.919785{col 26}{space 2} .0561063{col 37}{space 1}   34.22{col 46}{space 3}0.000{col 54}{space 4} 1.809818{col 67}{space 3} 2.029751
{txt}{space 8}d124 {c |}{col 14}{res}{space 2} 12.14693{col 26}{space 2} .4686319{col 37}{space 1}   25.92{col 46}{space 3}0.000{col 54}{space 4} 11.22842{col 67}{space 3} 13.06543
{txt}{space 8}d125 {c |}{col 14}{res}{space 2}-3.555576{col 26}{space 2} .1750886{col 37}{space 1}  -20.31{col 46}{space 3}0.000{col 54}{space 4}-3.898744{col 67}{space 3}-3.212409
{txt}{space 8}d126 {c |}{col 14}{res}{space 2} 7.333945{col 26}{space 2} .2368501{col 37}{space 1}   30.96{col 46}{space 3}0.000{col 54}{space 4} 6.869728{col 67}{space 3} 7.798163
{txt}{space 8}d127 {c |}{col 14}{res}{space 2} 5.772705{col 26}{space 2} .1534834{col 37}{space 1}   37.61{col 46}{space 3}0.000{col 54}{space 4} 5.471883{col 67}{space 3} 6.073527
{txt}{space 8}d128 {c |}{col 14}{res}{space 2} 8.209337{col 26}{space 2} .2889878{col 37}{space 1}   28.41{col 46}{space 3}0.000{col 54}{space 4} 7.642932{col 67}{space 3} 8.775743
{txt}{space 8}d129 {c |}{col 14}{res}{space 2} 2.399221{col 26}{space 2}  .140894{col 37}{space 1}   17.03{col 46}{space 3}0.000{col 54}{space 4} 2.123074{col 67}{space 3} 2.675368
{txt}{space 8}d130 {c |}{col 14}{res}{space 2}-7.139123{col 26}{space 2} .3690295{col 37}{space 1}  -19.35{col 46}{space 3}0.000{col 54}{space 4}-7.862407{col 67}{space 3}-6.415839
{txt}{space 8}d131 {c |}{col 14}{res}  (omitted)
{txt}{space 8}d132 {c |}{col 14}{res}{space 2}-3.215806{col 26}{space 2} .1352213{col 37}{space 1}  -23.78{col 46}{space 3}0.000{col 54}{space 4}-3.480835{col 67}{space 3}-2.950777
{txt}{space 8}d133 {c |}{col 14}{res}{space 2}-1.772563{col 26}{space 2} .1736605{col 37}{space 1}  -10.21{col 46}{space 3}0.000{col 54}{space 4}-2.112932{col 67}{space 3}-1.432195
{txt}{space 8}d134 {c |}{col 14}{res}{space 2}-3.955759{col 26}{space 2} .1685166{col 37}{space 1}  -23.47{col 46}{space 3}0.000{col 54}{space 4}-4.286045{col 67}{space 3}-3.625472
{txt}{space 8}d135 {c |}{col 14}{res}{space 2} 15.14177{col 26}{space 2} .4987962{col 37}{space 1}   30.36{col 46}{space 3}0.000{col 54}{space 4} 14.16414{col 67}{space 3} 16.11939
{txt}{space 8}d136 {c |}{col 14}{res}{space 2} 15.65835{col 26}{space 2} .5267897{col 37}{space 1}   29.72{col 46}{space 3}0.000{col 54}{space 4} 14.62586{col 67}{space 3} 16.69084
{txt}{space 8}d137 {c |}{col 14}{res}{space 2} 13.88141{col 26}{space 2} .4935372{col 37}{space 1}   28.13{col 46}{space 3}0.000{col 54}{space 4} 12.91409{col 67}{space 3} 14.84872
{txt}{space 8}d138 {c |}{col 14}{res}{space 2} 34.82659{col 26}{space 2} 1.380228{col 37}{space 1}   25.23{col 46}{space 3}0.000{col 54}{space 4}  32.1214{col 67}{space 3} 37.53179
{txt}{space 8}d139 {c |}{col 14}{res}{space 2} 6.511213{col 26}{space 2}  .306799{col 37}{space 1}   21.22{col 46}{space 3}0.000{col 54}{space 4} 5.909898{col 67}{space 3} 7.112528
{txt}{space 8}d140 {c |}{col 14}{res}{space 2}-3.663168{col 26}{space 2} .1411171{col 37}{space 1}  -25.96{col 46}{space 3}0.000{col 54}{space 4}-3.939752{col 67}{space 3}-3.386584
{txt}{space 8}d141 {c |}{col 14}{res}{space 2}  -4.2618{col 26}{space 2}  .171745{col 37}{space 1}  -24.81{col 46}{space 3}0.000{col 54}{space 4}-4.598414{col 67}{space 3}-3.925186
{txt}{space 8}d142 {c |}{col 14}{res}{space 2}-2.914143{col 26}{space 2} .1734977{col 37}{space 1}  -16.80{col 46}{space 3}0.000{col 54}{space 4}-3.254192{col 67}{space 3}-2.574094
{txt}{space 8}d143 {c |}{col 14}{res}{space 2} 4.310113{col 26}{space 2} .1918673{col 37}{space 1}   22.46{col 46}{space 3}0.000{col 54}{space 4} 3.934059{col 67}{space 3} 4.686166
{txt}{space 8}d144 {c |}{col 14}{res}{space 2} 8.056557{col 26}{space 2} .3169909{col 37}{space 1}   25.42{col 46}{space 3}0.000{col 54}{space 4} 7.435267{col 67}{space 3} 8.677848
{txt}{space 8}d145 {c |}{col 14}{res}{space 2} 5.611051{col 26}{space 2} .2353467{col 37}{space 1}   23.84{col 46}{space 3}0.000{col 54}{space 4}  5.14978{col 67}{space 3} 6.072322
{txt}{space 8}d146 {c |}{col 14}{res}{space 2} 4.705474{col 26}{space 2}  .227598{col 37}{space 1}   20.67{col 46}{space 3}0.000{col 54}{space 4}  4.25939{col 67}{space 3} 5.151558
{txt}{space 8}d147 {c |}{col 14}{res}{space 2} 12.24243{col 26}{space 2}  .413146{col 37}{space 1}   29.63{col 46}{space 3}0.000{col 54}{space 4} 11.43268{col 67}{space 3} 13.05218
{txt}{space 8}d148 {c |}{col 14}{res}{space 2} 2.008582{col 26}{space 2}  .072575{col 37}{space 1}   27.68{col 46}{space 3}0.000{col 54}{space 4} 1.866338{col 67}{space 3} 2.150827
{txt}{space 8}pov1 {c |}{col 14}{res}{space 2}-15.05237{col 26}{space 2} .5516136{col 37}{space 1}  -27.29{col 46}{space 3}0.000{col 54}{space 4}-16.13351{col 67}{space 3}-13.97123
{txt}biasthreat~r {c |}{col 14}{res}{space 2} .6874704{col 26}{space 2} .1436057{col 37}{space 1}    4.79{col 46}{space 3}0.000{col 54}{space 4} .4060083{col 67}{space 3} .9689324
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~r {c |}{col 14}{res}{space 2} .1915034{col 26}{space 2} .1300247{col 37}{space 1}    1.47{col 46}{space 3}0.141{col 54}{space 4}-.0633403{col 67}{space 3} .4463471
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~l {c |}{col 14}{res}{space 2} .4901189{col 26}{space 2} .1327254{col 37}{space 1}    3.69{col 46}{space 3}0.000{col 54}{space 4} .2299819{col 67}{space 3} .7502559
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~l {c |}{col 14}{res}{space 2} .0189891{col 26}{space 2} .1225061{col 37}{space 1}    0.16{col 46}{space 3}0.877{col 54}{space 4}-.2211184{col 67}{space 3} .2590966
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~y {c |}{col 14}{res}{space 2} .7412398{col 26}{space 2} .1556343{col 37}{space 1}    4.76{col 46}{space 3}0.000{col 54}{space 4} .4362023{col 67}{space 3} 1.046277
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~y {c |}{col 14}{res}{space 2}-.0463603{col 26}{space 2} .1429837{col 37}{space 1}   -0.32{col 46}{space 3}0.746{col 54}{space 4}-.3266031{col 67}{space 3} .2338826
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~e {c |}{col 14}{res}{space 2} .4006537{col 26}{space 2} .1289108{col 37}{space 1}    3.11{col 46}{space 3}0.002{col 54}{space 4} .1479932{col 67}{space 3} .6533143
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~e {c |}{col 14}{res}{space 2}-.1910427{col 26}{space 2} .1127271{col 37}{space 1}   -1.69{col 46}{space 3}0.090{col 54}{space 4}-.4119839{col 67}{space 3} .0298984
{txt}{space 12} {c |}
{space 6}female {c |}{col 14}{res}{space 2} .0683295{col 26}{space 2} .1235001{col 37}{space 1}    0.55{col 46}{space 3}0.580{col 54}{space 4}-.1737263{col 67}{space 3} .3103853
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0083773{col 26}{space 2} .0055367{col 37}{space 1}    1.51{col 46}{space 3}0.130{col 54}{space 4}-.0024745{col 67}{space 3} .0192291
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0660272{col 26}{space 2} .0454118{col 37}{space 1}   -1.45{col 46}{space 3}0.146{col 54}{space 4}-.1550327{col 67}{space 3} .0229783
{txt}{space 2}sufficient {c |}{col 14}{res}{space 2}-.1313749{col 26}{space 2} .0788516{col 37}{space 1}   -1.67{col 46}{space 3}0.096{col 54}{space 4}-.2859211{col 67}{space 3} .0231714
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .3007306{col 26}{space 2} .2061291{col 37}{space 1}    1.46{col 46}{space 3}0.145{col 54}{space 4}-.1032751{col 67}{space 3} .7047363
{txt}{space 2}darabmixed {c |}{col 14}{res}{space 2} .0152603{col 26}{space 2} .1698343{col 37}{space 1}    0.09{col 46}{space 3}0.928{col 54}{space 4}-.3176089{col 67}{space 3} .3481294
{txt}{space 3}religious {c |}{col 14}{res}{space 2}-.3246257{col 26}{space 2} .1043191{col 37}{space 1}   -3.11{col 46}{space 3}0.002{col 54}{space 4}-.5290874{col 67}{space 3}-.1201641
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-18.14912{col 26}{space 2} .9025986{col 37}{space 1}  -20.11{col 46}{space 3}0.000{col 54}{space 4}-19.91818{col 67}{space 3}-16.38006
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. ologit biasorder c.pov1##c.biasthreat_labor c.pov1##c.biasthreat_fiscal c.pov1##c.biasthreat_security c.pov1##c.biasthreat_culture female age education sufficient unemployed darabmixed religious, cluster(dst)

{txt}note: pov1 omitted because of collinearity
note: pov1 omitted because of collinearity
note: pov1 omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-2121.9711}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1992.2638}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1986.7236}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1986.7058}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1986.7058}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}      2311
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}    243.51
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-1986.7058{txt}{col 51}Pseudo R2{col 67}= {res}    0.0637

{txt}{ralign 78:(Std. Err. adjusted for {res:150} clusters in dst)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}   biasorder{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}pov1 {c |}{col 14}{res}{space 2}-.0272076{col 26}{space 2} .0700542{col 37}{space 1}   -0.39{col 46}{space 3}0.698{col 54}{space 4}-.1645113{col 67}{space 3} .1100962
{txt}biasthreat~r {c |}{col 14}{res}{space 2}  .508964{col 26}{space 2} .1091696{col 37}{space 1}    4.66{col 46}{space 3}0.000{col 54}{space 4} .2949956{col 67}{space 3} .7229325
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~r {c |}{col 14}{res}{space 2} .1787996{col 26}{space 2} .0850904{col 37}{space 1}    2.10{col 46}{space 3}0.036{col 54}{space 4} .0120255{col 67}{space 3} .3455738
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~l {c |}{col 14}{res}{space 2} .2861013{col 26}{space 2} .1097889{col 37}{space 1}    2.61{col 46}{space 3}0.009{col 54}{space 4}  .070919{col 67}{space 3} .5012836
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~l {c |}{col 14}{res}{space 2}-.0685027{col 26}{space 2}  .095515{col 37}{space 1}   -0.72{col 46}{space 3}0.473{col 54}{space 4}-.2557087{col 67}{space 3} .1187033
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~y {c |}{col 14}{res}{space 2}  .640772{col 26}{space 2} .1128007{col 37}{space 1}    5.68{col 46}{space 3}0.000{col 54}{space 4} .4196866{col 67}{space 3} .8618573
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~y {c |}{col 14}{res}{space 2}-.0702557{col 26}{space 2} .0958976{col 37}{space 1}   -0.73{col 46}{space 3}0.464{col 54}{space 4}-.2582116{col 67}{space 3} .1177002
{txt}{space 12} {c |}
{space 8}pov1 {c |}{col 14}{res}  (omitted)
{txt}biasthreat~e {c |}{col 14}{res}{space 2} .4735668{col 26}{space 2} .1042464{col 37}{space 1}    4.54{col 46}{space 3}0.000{col 54}{space 4} .2692476{col 67}{space 3} .6778859
{txt}{space 12} {c |}
{space 6}c.pov1#{c |}
{space 10}c. {c |}
biasthreat~e {c |}{col 14}{res}{space 2} -.188724{col 26}{space 2} .0805012{col 37}{space 1}   -2.34{col 46}{space 3}0.019{col 54}{space 4}-.3465034{col 67}{space 3}-.0309446
{txt}{space 12} {c |}
{space 6}female {c |}{col 14}{res}{space 2} .1956317{col 26}{space 2} .0987346{col 37}{space 1}    1.98{col 46}{space 3}0.048{col 54}{space 4} .0021155{col 67}{space 3} .3891479
{txt}{space 9}age {c |}{col 14}{res}{space 2} .0094137{col 26}{space 2} .0045977{col 37}{space 1}    2.05{col 46}{space 3}0.041{col 54}{space 4} .0004023{col 67}{space 3} .0184251
{txt}{space 3}education {c |}{col 14}{res}{space 2}-.0373842{col 26}{space 2} .0349482{col 37}{space 1}   -1.07{col 46}{space 3}0.285{col 54}{space 4}-.1058814{col 67}{space 3} .0311131
{txt}{space 2}sufficient {c |}{col 14}{res}{space 2}-.0978497{col 26}{space 2} .0704417{col 37}{space 1}   -1.39{col 46}{space 3}0.165{col 54}{space 4}-.2359129{col 67}{space 3} .0402135
{txt}{space 2}unemployed {c |}{col 14}{res}{space 2} .0135662{col 26}{space 2} .1743533{col 37}{space 1}    0.08{col 46}{space 3}0.938{col 54}{space 4}-.3281599{col 67}{space 3} .3552924
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